How to implement random forest in shogun

In this recipe, we shall learn how can we implement a random forest model in shogun. We shall also take a look at an example for better clarity.

Get access to Data Science projects View all Data Science projects
MACHINE LEARNING RECIPES DATA CLEANING PYTHON DATA MUNGING PANDAS CHEATSHEET     ALL TAGS

Recipe Objective: How to implement random forest in shogun?

This recipe explains how to implement random forest in shogun.
For more related projects-
Project 1
Project 2

Get Access to Plant Species Identification Project using Machine Learning

Random Forest

Random forest constitutes various individual decision trees that operate as an ensemble. These individual trees in random forest divide class prediction, and the class which gains the maximum votes becomes the model's prediction.

x_train = RealFeatures(feats_train)
x_test = RealFeatures(feats_test)
y_train = MulticlassLabels(labels_train)
y_test = MulticlassLabels(labels_test)

vote = MajorityVote()
rf = RandomForest(x_train, l_train, 100)
rf.set_combination_rule(vote)

rf.train()
predict = rf.apply_multiclass(x_test)
accuracy = MulticlassAccuracy()
acc = accuracy.evaluate(predict, y_test)

What Users are saying..

profile image

Ameeruddin Mohammed

ETL (Abintio) developer at IBM
linkedin profile url

I come from a background in Marketing and Analytics and when I developed an interest in Machine Learning algorithms, I did multiple in-class courses from reputed institutions though I got good... Read More

Relevant Projects

Machine Learning Projects
Data Science Projects
Python Projects for Data Science
Data Science Projects in R
Machine Learning Projects for Beginners
Deep Learning Projects
Neural Network Projects
Tensorflow Projects
NLP Projects
Kaggle Projects
IoT Projects
Big Data Projects
Hadoop Real-Time Projects Examples
Spark Projects
Data Analytics Projects for Students

You might also like

Data Science Tutorial
Data Scientist Salary
How to Become a Data Scientist
Data Analyst vs Data Scientist
Data Scientist Resume
Data Science Projects for Beginners
Machine Learning Engineer
Machine Learning Projects for Beginners
Datasets
Pandas Dataframe
Machine Learning Algorithms
Regression Analysis
MNIST Dataset
Data Science Interview Questions
Python Data Science Interview Questions
Spark Interview Questions
Hadoop Interview Questions
Data Analyst Interview Questions
Machine Learning Interview Questions
AWS vs Azure
Hadoop Architecture
Spark Architecture

Relevant Projects

Image Classification Model using Transfer Learning in PyTorch
In this PyTorch Project, you will build an image classification model in PyTorch using the ResNet pre-trained model.
View Project Details
Insurance Pricing Forecast Using XGBoost Regressor
In this project, we are going to talk about insurance forecast by using linear and xgboost regression techniques.
View Project Details
Time Series Forecasting with LSTM Neural Network Python
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.
View Project Details
Build an optimal End-to-End MLOps Pipeline and Deploy on GCP
Learn how to build and deploy an end-to-end optimal MLOps Pipeline for Loan Eligibility Prediction Model in Python on GCP
View Project Details
Recommender System Machine Learning Project for Beginners-2
Recommender System Machine Learning Project for Beginners Part 2- Learn how to build a recommender system for market basket analysis using association rule mining.
View Project Details
Build Customer Propensity to Purchase Model in Python
In this machine learning project, you will learn to build a machine learning model to estimate customer propensity to purchase.
View Project Details
Loan Default Prediction Project using Explainable AI ML Models
Loan Default Prediction Project that employs sophisticated machine learning models, such as XGBoost and Random Forest and delves deep into the realm of Explainable AI, ensuring every prediction is transparent and understandable.
View Project Details
Build a Review Classification Model using Gated Recurrent Unit
In this Machine Learning project, you will build a classification model in python to classify the reviews of an app on a scale of 1 to 5 using Gated Recurrent Unit.
View Project Details
NLP Project to Build a Resume Parser in Python using Spacy
Use the popular Spacy NLP python library for OCR and text classification to build a Resume Parser in Python.
View Project Details
Learn to Build an End-to-End Machine Learning Pipeline - Part 2
In this Machine Learning Project, you will learn how to build an end-to-end machine learning pipeline for predicting truck delays, incorporating Hopsworks' feature store and Weights and Biases for model experimentation.
View Project Details